In India (among others), honking is essential to reducing crashes
We often greatly underestimate / undervalue the role of our ears relative to vision. As my film director friend says, 80% of the impact in a movie is in the sound
The biggest surprise I had in attempting to distribute my first Android app is how difficult it is to get beta-testers through the "standard" channels. It requires a 1 week review and 25 beta-users invited by email addresses
In contrast, Apple has a ~48 hour turnaround for reviews before you can upload to TestFlight and distribute a beta with a link
Not sure if I am in some "trusted developer" cohort on iOS but not Android - but the difference was enough for me to stop trying on Android
you are conflating equity and equality. its equalising in the sense that it democratises access to data, knowledge. but that does not mean it will end up with everyone being equal in terms of wealth.
But it won't even do that. In the pursuit of extracting maximal capital, better models with "better" knowledge will be gated behind higher prices. If you pay more, you get more.
"Swarm of autonomous drones kills 3 buildings of civilians, Silicon Valley is shocked, CEO's offer condolences" is a byline waiting to happen[1]
The administration and the executives will make justifications like:
- "We didn't think they would go haywire"
- "Fewer people died than with an atomic bomb"
- "A junior person gave the order to the drones, we fired them"
- "Look at what Russia and China are doing"
Distracting from the fact that the purpose of spending $1.5T/year on AI weapons (technology that has the sole purpose of threatening/killing humans) run by "warfighters" working for the department of war
At no point will any of the decision makers be held to account
The only power we have as technologists seeking "AI alignment" is to stop building more and more powerful weapons. A swarm of autonomous drones (and similar technologies) are not an inevitability, and we must stop acting as if it is. "It's gonna happen anyways, so I might as well get paid" is never the right reason to do things
This feels like a fair question (perhaps not perfect wording, but no adhominem or disingenuity)
More broadly, we are overbuilding infra on highly inefficient silicon (at a time when designing silicon is easier than ever) and energy stacks _before_ the market is naturally driving it. (with assets that depreciate far faster than railroads). Just as China overbuilt Shenzhen
I have heard (unconfirmed) that the US is importing CNG engines from India for data center buildouts. I loved summers in my youth in Bombay and the parallax background have been great for photography, but the air is no fun to breathe (and does a kicker on life-expectancy to boot)
If we aren't asking these questions here, are they being asked? Don't bite the hand that feeds?
On device models (deepseek-coder, etc) are very good // better than the old way of using stack overflow on the internet. I have been quite productive on long haul flights without internet!
You're an engineer, your goal is to figure stuff out using the best tools in front of you
Humans are resilient, they reliably perform (and throw great parties) in all sorts of chaotic conditions. Perhaps the thing that separates us most from AI is our ability to bring out our best selves when baseline conditions worsen
I know this gets asked all the time, but what is your preferred workflow when using local models? I was pretty deep into it early on, with Tabby and Continue.dev, but once I started using Claude Code with Opus it was hard to go back. I do the same as you, and still use them on flights and whatnot, but I think my implementation could be improved.
Developer here. This was a blast to work on over the past few months in collaboration with the Magenta team. Built using a C++/JUCE foundation and a React frontend
> The researchers used microphones to record healthy and stressed tomato and tobacco plants, first in a soundproofed acoustic chamber and then in a noisier greenhouse environment. They stressed the plants via two methods: by not watering them for several days and by cutting their stems. After recording the plants, the researchers trained a machine-learning algorithm to differentiate between unstressed plants, thirsty plants, and cut plants.
This is interesting but obviously very different from the suffering that animals are experiencing.
We often greatly underestimate / undervalue the role of our ears relative to vision. As my film director friend says, 80% of the impact in a movie is in the sound
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